enhancement of optimized linked state routing protocol for energy ...

ENHANCEMENT OF OPTIMIZED LINKED STATE ROUTING PROTOCOL FOR ENERGY CONSERVATION Mayur Tokekar1 and Radhika D. Joshi2 1

Department of Electronics and Tele-communication, College of Engineering, Pune, India

2

Department of Electronics and Tele-communication, College of Engineering, Pune, India

[email protected]

[email protected]

ABSTRACT Mobile Ad-hoc network (MANET) is infrastructure less network in which nodes are mobile, self reconfigurable, battery powered. As nodes in MANET are battery powered, energy saving is an important issue. We are using routing protocol to save energy so as to extend network lifetime. We have extended original Optimized Linked State Routing (OLSR) protocol by using two algorithms and named it as Enhancement in OLSR using Residual Energy approach (EOLSRRE) and Enhancement in OLSR using Energy Consumption approach (EOLSR-EC). To analyze relative performance of modified protocol EOLSR-RE and EOLSR-EC over OLSR, we performed various trials using Qualnet simulator. The performance of these routing protocols is analyzed in terms of energy consumption, control overheads, end to end delay, packet delivery ratio. The modified OLSR protocol improves energy efficiency of network by reducing 20 % energy consumption and 50% control overheads.

KEYWORDS MANET, OLSR, EOLSR-RE, EOLSR-EC, QoS parameters.

1. INTRODUCTION Ad-hoc network is one of the emerging trends in wireless communication. In conventional wireless communication there is need of base station for communication between two nodes. These base station leads to more infrastructure and more cost. An ad hoc network facilitates communication between nodes without the existence of an established infrastructure. Nodes are connected randomly using ad-hoc networking and routing among the nodes is done by forwarding packets from one to another which is decided dynamically. In general, MANET’s are formed dynamically by an autonomous system of mobile nodes that are connected via wireless links without using any centralized administration [1]. Mobile nodes that are within each other’s radio range communicate directly via wireless links, while those that are far apart rely on other nodes to relay messages as routers. Node mobility in an ad hoc network causes frequent changes of the network topology. The scopes of the ad-hoc network are also associated with dynamic topology changes, bandwidth-constrained, energy constrained operation, limited physical security, mobility-induced packet losses, limited wireless transmission range, broadcast nature of the wireless medium, hidden terminal problem, packet losses due to transmission errors [2]. In Energy constrained operations, it is important to save energy which results in improvement in network lifetime. For example, in battle fields soldiers are unable to charge node batteries so there D.C. Wyld, et al. (Eds): CCSEA 2011, CS & IT 02, pp. 305–319, 2011. © CS & IT-CSCP 2011

DOI: 10.5121/csit.2011.1228

306

Computer Science & Information Technology (CS & IT)

is need for them to save battery power in such a way that communication can be possible for longer time. To improve network lifetime there are different methodologies used at different layers of OSI model. Network layer is used for routing of packets from source to destination. There are number of routing protocols defined in MANET, for example DSDV, AODV, DSR, OLSR, ZRP etc. The main objective is to design routing protocol in such a way that it works effectively in energy constrained applications. The main focus is on OLSR routing protocol modification in network layer. The paper is organized as follows. Section II explains different types of routing protocols. Section III discusses the basics of OLSR protocol and study of related energy aware techniques. Section IV discusses the proposed modification in OLSR. Section V represents the simulation details and QoS parameters. Section VI discusses results obtained by Qualnet simulator. Finally section VII concludes the paper with future work in section VIII.

2. CLASSIFICATION OF ROUTING PROTOCOL In MANET, each node between source and destination acts as routers. The routing of data packets from source to destination are controlled by different routing protocols. Different routing protocols are classified as shown in Figure;

Figure 1.Classification of Routing Protocols

2.1. Proactive routing protocols In proactive routing, each node has one or more tables that contain the latest information of the routes to any node in the network. Each node maintain routing tables and respond to the changes in the network topology by propagating updates throughout the network in order to maintain a consistent view of the network. Many proactive routing protocols have been proposed, for e.g. Destination Sequence Distance Vector (DSDV), Optimized Linked State Routing (OLSR) and so on.

2.2. Reactive protocols Unlike proactive routing protocols, the reactive routing protocols create routes once a node wants to transmit data to a destination. The source node initiates route discovery process by flooding route query within the network. When the destination is reached, route reply request will be sent


307

back to the source. Once the route has been found, it is maintained until either destination becomes inaccessible or the route is no longer desired then route discovery process will be invoked again. Several reactive protocols have been proposed such as Dynamic Source Routing protocol (DSR), Ad hoc On-demand Distance Vector (AODV), Temporary Ordered Routing Algorithm (TORA), and so on.

2.3. Hybrid routing protocols In such network, hybrid routing protocols, i.e. combining proactive and reactive routing protocols, are used in order to take advantages on these two routing protocols where proactive maintains route in a cluster and reactive maintains route between clusters. Several hybrids routing protocols have been proposed such as Zone Routing Protocol (ZRP), Zone-based Hierarchical Link State (ZHLS) and so on, but the most popular protocol is ZRP.

3. OLSR OVERVIEW AND RELATED WORK OLSR [3] is proactive in nature, having routes immediately available in each node for all destinations in the network. OLSR is an optimization of pure link state routing protocol like Open Shortest Path First (OSPF) [4]. This optimization is related to concept of multipoint relay (MPR). A multipoint relay reduces the size of control messages. The use of MPRs also minimizes flooding of control traffic. Multipoint relays forward control messages, providing advantage of reduction in number of retransmissions of broadcast control messages. OLSR contains two types of control messages: neighborhood and topology messages, known as Hello messages and Topology Control (TC) messages. OLSR provides two main functionalities: Neighbor Discovery and Topology Dissemination. With the help of these two functionalities, each node computes routes to all known destinations.

Figure 2.Selection of MPR and Broadcasting TC packets

3.1. Selection of Multipoint Relay (MPR) using HELLO messages Each node periodically broadcasts Hello messages, containing list of neighbors known to node and link status. The link status can be either symmetric or asymmetric, multipoint relay, or lost link. The Hello messages are received by all one-hop neighbors and not forwarded. Hello messages discover one-hop neighbors as well as its two-hop neighbors. Hello messages are broadcast at regular interval (Hello_interval). The neighborhood and two hop neighborhood information has holding time (Neighbor_hold_time), after which it is not valid. With the help of this information node selects its own set of MPRs among one-hop neighbors. Multipoint relays computed whenever there is change in one-hop neighborhood and two-hop neighborhood. MPR is one-hop neighbors with symmetric link, such that all two-hop neighbors has symmetric link with

308


multipoint relays. Figure 2 shows selection of MPR node using HELLO packets. Node is selected as MPR node when it has willingness high i.e. W_HIGH or default i.e. W_DEFAULT otherwise rejected.

3.2. Significance of TC messages Each node of the network maintains topological information about the network obtained with help of TC messages. Each node selected as MPR, broadcasts TC message at regular interval (TC_interval). The TC message originated from node which declares MPR selectors of that node. If change occurs in MPR selector set, then TC message can be sent earlier than pre-specified interval. The TC messages are sent to all nodes in the network by taking advantage of MPR nodes to avoid number of retransmissions. Thus, a node is reachable directly or via its MPRs. The topological information collected in each node has holding time (Top_hold_time), after which information is not valid. Figure 2 shows broadcasting of TC message with the help of MPR nodes.

3.3. Route Calculation The neighbor information and the topology information are refreshed periodically, and they enable each node to compute the routes to all known destinations. These routes are computed with Dijkstra’s shortest path algorithm [5]. Hence, they are optimal with respect to the number of hops. Moreover, for any route, any intermediate node on this route is a MPR of the next node. The routing table is computed whenever there is a change in neighborhood or topology information.

3.4. HELLO and TC packet format Reserved Link Code

Reserved

Htime Willingness Link Message size

ANSN

Reserved

Advertised Neighbor Main Address

Neighbor Interface Address

Advertised Neighbor Main Address

Neighbor Interface Address

..............

Figure 3.OLSR HELLO Packet Format

Figure 4.OLSR TC Packet Format

Figure 3 shows HELLO packet format for OLSR. The Reserved portion in HELLO packets is used for further modification. Htime specifies time before transmission of next HELLO packet. Willingness entry specifies node willingness to forward traffic. Link Code gives the information about link between sender node and neighbor node. It represents status of neighbor node. Neighbor interface address denotes address of interface of neighbor node. Link Message size gives total length of link messege. Figure 4 represents TC packet format for OLSR. Advertised Neighbor Sequence Number (ANSN) which increments sequence number whenever there is change in neighbor set. Reserved field is used for further modification in TC packets. Advertised Neighbor Main Address field contains main address of neighbor node.

3.5. Survey of Energy Efficient Routing Schemes There are various ways to save energy from physical layer to application layer. In network layer energy saving can be possible by selecting energy efficient path for sending data from source to destination. The surveys of different energy saving techniques are discussed as below;


309

I. Stojmenovic and X. Lin [6] proposed localized power aware routing algorithms which are devised on the assumption that each network node has accurate information about the location of its neighbors and the destination node. Nodes exchange location information via control messages. Three algorithms are proposed in [6]: • Power-efficient routing: Each node decides to forward packets that are intended for a certain destination to a neighbor based on the minimum transmission power between this sending node and its neighbors. • Cost-efficient routing: The node chooses the neighbor to send to, if the destination is not within reach, based on a cost function that can consist, for example, the sum of the cost of sending node to this neighbor plus the estimated cost of the route from the neighbor up to the destination. This latter part of the cost is assumed to be proportional to the number of hops in between. • Power-cost efficient routing algorithms: Uses a combination of the two above metrics, in the form of either the product or the sum of these metrics. C.K.Toh [7] explains MTPR (Minimum Total Transmission Power Routing) mechanism, where route having minimum transmission power is selected. The information of total energy consumption is provided along route using HELLO and TC packets in OLSR. Based on this information route is selected for sending data to destination. CMMBCR (Conditional Max Min Battery Capacity Routing) [18] mechanism considers both the total transmission energy consumption of routes and the remaining power of nodes. When all nodes in some possible routes have sufficient remaining battery capacity, i.e. above a threshold, route with minimum total transmission power among the routes is chosen. Since less total power is required to forward packets for each connection, the load for most of the nodes must be reduced, and their by lifetime will be extended. But, if all routes have nodes with low battery capacity i.e. below the defined threshold, a route including nodes with lowest battery capacity must be avoided to extend the lifetime of these nodes. Energy efficient technique for selection of MPR nodes is proposed by Saoucene Mahfoudh and Pascale Minet [8] where node considers residual energy for selection of MPR. The node having minimum residual energy is not selected as MPR. There are three policies are considered for selection of MPR. • • •

E: considers only residual energy of node itself. M1E: considers weighted residual energy of node itself and 1-hop neighbors. M2E: M2E considers weighted residual energy of node, 1-hop and 2-hop neighbors.

Minimum Drain Rate (MDR) mechanism is proposed for selection of path having maximum lifetime value in [9]. MDR mechanism calculates cost function which takes into account the drain rate index and residual battery power. Maximum lifetime value of a given path is determined by minimum cost value over the path. From the set routes, the route having highest maximum lifetime is selected for transmission. The J. H. Chang and L. Tassiulas [10] proposed two algorithms with the aim of extending the network lifetime via optimizing the routing from an energy consumption perspective. 1. Flow augmentation (FA) algorithm: is based on creating a link cost function. This function considers the following parameters: energy cost for unit flow over the link, the initial energy and the remaining energy at the transmitting node. A good candidate for the

310


selected path should consume less energy and should avoid nodes with low remaining energy. 2. Flow redirection (FR) algorithm: If we have multiple sources and destinations, then under the optimal flow (i.e. minimum lifetime over all nodes is maximized) the minimum lifetime of every path from the source to the destination is the same. The minimum lifetime of this set of paths can be increased by redirecting an arbitrarily small amount of flow to the paths whose lifetime is longer than these paths such that the minimum lifetime of the latter path after the redirection is still longer than the system lifetime before the redirection.

4. PROPOSED IDEA In this section, the modification steps for OLSR protocol are discussed. The modified protocol is named as EOLSR. The OLSR protocol is modified in two processes i.e. while selecting MPR nodes and while calculating route for forwarding data.

4.1. MPR Selection The existing OLSR consumes more energy in energy constrained applications which results in less network lifetime. To improve network lifetime as well as energy efficiency OLSR is modified by using two approaches as below; 1. By setting threshold for Residual Energy 2. By setting threshold for Energy Consumption For MPR selection we have decided a threshold value, which is one third of initial energy for both residual energy and energy consumption approach. •

If the residual energy of node is less than threshold value then node having LOW-MPRWILL while residual energy of node is greater than threshold value than node having HIGH-MPR-WILL.

•

If the energy consumed by node is less than threshold value then node having HIGHMPR-WILL while residual energy of node is greater than threshold value than node having LOW-MPR-WILL.

4.2. New HELLO and TC packet format Residual Energy Link Code

Reserved

Htime

Willingness

Link message size

Energy

Htime Willingness

Consumption LinkCode Reserved

Link message size

Neighbour Interface Address




Figure 5.EOLSR-RE HELLO Packet Format

ANSN

Residual Energy

Figure 6.EOLSR-EC HELLO Packet Format

ANSN

Energy Consumption

Advertised Neighbour Main Address




..............

..............

Figure 7.EOLSR-RE TC Packet Format

Figure 8.EOLSR-EC TC Packet Forma


311

HELLO packets are used for selection of MPR nodes. For selection of MPR each node having, • Highest residual energy • Lowest energy consumption There is need to update residual energy of each node at regular interval. For this purpose the value of residual energy and energy consumed by node is included in HELLO packet as shown in Figure 5 and Figure 6 respectively. The reserved part in OLSR HELLO packet format as shown in Figure 3 is assigned to residual energy in EOLSR-RE and energy consumption in EOLSR-EC. Each node sends HELLO packet with entry for current residual energy and depending on threshold value set it selects MPR node. The reserved part in TC packet as shown in Figure 4 is modified with entry for residual energy and energy consumption of node as shown in Figure 7 and Figure 8 respectively. The TC packets are forwarded to entire network with the help of MPR nodes. The TC packets are used to disseminate topology information over entire network. The modified TC packet format distributes residual energy of each node and energy consumed by each node over entire network. After knowing topology information for each node in network the route calculation is performed. 4.3. Flow Chart for Residual Energy and Energy Consumption Approach

Figure 9.Flow Chart for residual Energy and Energy Consumption Approach

312


5. SIMULATOR DETAILS AND QOS PARAMETERS QualNet Simulator [11] is a set of tools for modelling large wired and wireless networks. QualNet (formerly GloMoSim) is a commercial program for wired and wireless network simulations by Scalable Network Technologies. It consists of three layers: • • •

The simulation kernel (a discrete event scheduler) as basic layer. The model libraries as second layer. The top layer is defined by the QualNet Developer GUI.

It has different tools such as the Scenario Designer, Animator, or Analyzer. QualNet provides comprehensive graphical environment allows one to create and visualize network scenarios, and to analyze the simulation results in one single GUI. The simulation run is visualized in the tool ‘Animator’. During the simulation run, several outputs can be activated or deactivated in Animator such as broadcast messages, successfully received packets (packet flow), dropped packets. Output of the simulation runs are different output files containing different information. The primary output file (.stat) contains statistical information. Depending on the simulation and configuration, other files can be created.

5.1. Simulation Models A simulation model consists of Energy Model, Battery Model, Traffic Model and Mobility Model. The specifications for these models used in our experimentation are discussed as below; 5.1.1. Energy Model The User-defined energy model [12] is a configurable model that allows the user to specify the energy consumption parameters of the radio in different power modes. The total power required for transmission, reception, idle (node is listening the medium) and sleep (node is not capable to detect signals so communication is not possible) modes is given in Table. Table 1. Power requirement for different modes Power requirement for different modes (Supply voltage 3V) Power Transmission Reception Power Idle Power Sleep Power

Power Values 0.84 Watts 0.612 Watts 0.534 Watts 0.042 Watts

5.1.2. Battery Model: Linear Model Nodes in the mobile ad-hoc network are battery operated. Hence, battery models are useful tools for such types of system design approach; because they enable analysis of the discharge behaviour of the battery under different design choices for example power management policies. We used Linear Battery Model for the experimentation. 5.1.3. Traffic Model Constant Bit Rate (CBR) sources represent voice sources and ftp sources are the ones used for file transfer applications. We focus on Constant Bit Rate (CBR).The packet size is limited to 512 bytes. The source-destination pairs are chosen randomly over the network. The sourcedestination numbers are fixed (called connection number).


313

5.1.4. Mobility Model We used random way point mobility model where nodes in network moves randomly in any direction with given speed.

5.2. Quality of Service (QoS) Parameters 5.2.1. Average End to End Delay It is the average source-to-destination data packet delay including propagation and queuing delay [13]. For a highly interactive application such as IP phone, end-to-end delays smaller than 150 ms are not perceived by human listeners. Lesser end-to-end delay implies better performance. 5.2.2. Packet Delivery Fraction (PDF) Ratio of number of packets successfully received by destination nodes to number of packets sent by source nodes.PDF describes information about packet loss rate [14]. Higher value of PDR for network indicates the better reliability of protocol. 5.2.3. Energy Consumed Total energy consumed required to transmit all data packets to destination node. To achieve better energy efficiency, energy consumed should be as low as possible [15]. The less energy consumption by nodes extends the network lifetime i.e. nodes in the network can communicate for longer period. 5.2.4. Control Overheads The total number of routing packets transmitted for each delivered data packet [16]. Lesser control overheads indicate that saving of energy in the network. Larger overheads utilise large bandwidth which cause congestion in the network. Hence, control overheads should be less.

6. SIMULATION RESULTS AND PERFORMANCE ANALYSIS 6.1. Impact of Variation of Node Density and Node Speed To analyze performance of EOLSR-RE and EOLSR-EC over OLSR, the numbers of nodes as well as node speed are varied and compared with the help of QoS parameter discussed in section 5. Numbers of nodes are varied from 20 to 100 for fixed area to analyse performance of sparse and dense network. Speed is varied to study the impact mobility of node on network. Number of connections for simulations should be half as that of nodes present. Table 2.Simulation Table Parameters

Variation of Number of Nodes

Variation of Node speed

Variation of Number of Connections

Area Nodes Node Speed Simulation Time

870x870 20,40,60,80,100 3m/s 500 s

870x870 50 1,3,5,8.10 m/s 500 s

870x870 50 3 m/s 500 s

314


Traffic Type Traffic Sources Packet Rate Initial Power Routing Protocol

CBR 9,18,27,36,45 2 packets/sec 30 mAHr EOLSR,OLSR

CBR 20 2 packets/sec 30 mAHr EOLSR,OLSR

CBR 16,18,20,22,24 2 packets/sec 30 mAHr EOLSR,OLSR

6.1.1. Average end to end delay

Figure 10: Impact of Variation of Number of Nodes and Node Speed on Average end to end delay

Figure10 depicts end to end delay for EOLSR-RE, OLSR and EOLSR-EC protocols for number of nodes from 20 to 100 and node speed 1 to 10 m/s. It is clear that EOLSR-RE has shortest delay than EOLR-EC and OLSR. On an average EOLSR-EC shows better performance than OLSR after 80 nodes and for all speed. For sparse network delay is almost same for all three protocols while for dense network EOLSR-RE shows shortest delay. Table 3.Impact of variation of Number of Connections on Average end to end delay No. of Connection

Average end to end delay EOLSRRE

OLSR

EOLSREC

% Change in EOLSR-RE

% Change in EOLSR-EC

16

20.6159

22.2534

21.5053

-7.358

-3.361733

18 20

23.4997 26.8916

26.8511 32.0454

24.3007 28.5996

-12.48 -16.08

-9.498307 -10.75287

22

33.0379

38.0543

35.3379

-13.18

-7.138221

24

37.895

41.6945

40.7432

-9.11

-2.281596

We have varied number of connection from 16 (i.e. around 32 nodes). This is because the OLSR has better performance in dense network [17]. As shown in Table 3, the average end to end delay increases with increase in number of connections. On an average, there is 15% less delay in EOLSR-RE and 10% less delay in EOLSR-EC. It is seen that for high traffic network delay has higher value in all three protocols.


315

Note: In presented Tables, +ve sign shows higher value of EOLSR parameter as compared to OLSR while –ve sign shows lesser value. 6.1.2. Packet Delivery Fraction (PDF)

Figure 11: Impact of Variation of Number of Nodes and Node Speed on Packet Delivery Fraction

The impact of variation of nodes and node speed on packet delivery is as shown in Figure 11.It is seen that packet delivery is almost same over the entire node range and it shows decreasing trend. For lower speed EOLSR-RE has better packet delivery than OLSR and EOLSR-EC while for higher speed packet delivery is almost same for all three protocols. It is observed that PDF falls with increasing node speed. Table 4.Impact of variation of Number of Connections on Packet Delivery Fraction (PDF) No. of Connection

Packet Delivery Fraction (PDF) EOLSRRE

OLSR

EOLSR-EC



16

89.375

91.2624

89.553

- 2.07

-1.873061

18

90.3888

91.1444

90.5323

-0.83

-0.671572

20

88.86

91.08

90.221

-2.43

-0.943127

22

87.909

91.5272

88.502

-3.95

-3.305247

24

85.675

89.125

87.993

-3.87

-1.270126

As shown in Table 4, packet delivery is above 90% in case of all three protocols which indicates there is slight change in packet delivery with increase in number of connections.

316


6.1.3. Energy Consumption

Figure 12: Impact of Variation of Number of Nodes and Node Speed on Energy Consumption Figure 12 shows effect of node variation and speed variation on energy consumption. In case of EOLSR-RE, energy consumption has lesser value than OLSR and EOLSR-EC which is almost 20% less than OLSR and 10% less than EOLSR-EC. It is seen that for three protocols there is increasing trend of energy consumption for both cases number of nodes and node speed variation.

Table 5.Impact of variation of number of connections on Energy Consumption No. of Connection

Energy Consumption EOLSRRE

OLSR

EOLSR-EC



16

10.3874

10.5285

10.4421

-1.34

-0.82063

18

9.98939

12.5364

10.2235

-20.27

-18.44948

20

10.7527

13.9693

11.9932

-22.99

-14.14602

22

13.5147

15.7888

14.3235

-14.38

-9.280629

24

15.6768

17.9791

16.5433

-12.79

-7.985939

The energy consumption reduces by 20% in EOLSR-RE and 15% in EOLSR-EC as shown in Table 5. It is seen that energy consumption increases with increase in number of connections.


317

6.1.4. Control Overheads

Figure 13: Impact of Variation of Number of Nodes and Node Speed on Control Overheads The control overheads for EOLSR-RE are 50% less than OLSR and 25% less than EOLSR-EC as shown in Figure 13. The control overheads are increases with increase in number of nodes while remains constant for increase in node speed. Table 6.Impact of variation of number of connections on Control Overheads No. of Connection

Control Overheads EOLSRRE

OLSR

EOLSREC


% Change in EOLSREC

16

7305.6

15520.38

10000.21

-52.92

-35.56723

18

7364.44

15978.4

10124.42

-53.91

-36.63683

20

7228.82

15922.2

10342.23

-54.59

-35.04522

22

7307.78

16006.14

10355.32

-54.34

-35.30408

24

7352

16345.9

10234.21

-55.02

-37.38974

There is almost 50% reduction in control overheads in EOLSR-RE and 35% reduction in EOLSR-EC as shown in Table 6. Control overheads remains constant with increase in number of connections which indicates there is less impact of number of connections on control overheads.

7. CONCLUSION In this paper, we compared EOLSR-RE and EOLSR-EC over OLSR with the help of performance metrics such as packet delivery fraction, average end to end delay, total energy consumption, control overheads. Simulations have performed for different network conditions to compare performance of EOLSR-RE and EOLSR-EC over OLSR. Experimental results demonstrate that the proposed EOLSR-RE protocol results in a 20 percent and EOLSR-EC protocol results in 10 percent of energy saving and this saving is obtained starting from the transmission of the first packet. Subsequent packets transmitted using the

318


EOLSR-RE and EOLSR-EC protocol will result in further energy savings. From this discussion, we can say that EOLSR-RE is best protocol in terms of energy efficiency. From experimental results, we can say that packet delivery is inversely proportional to node density, node speed. Average end to end delay is less sensitive to node speed while highly sensitive to node density. The average energy consumption increases with node density, node speed. Control overheads are directly proportional to node density while it remains constant for variation of node speed. From this discussion we can conclude that EOLSR-RE is best for moderately dense (in area 870x870) network having low speed (1 m/s to 5 m/s), low packet rate (2 packets/second) and high traffic i.e. large number of connections. From results it is observed that we have successfully modified OLSR with 15% less end to end delay, 50% less control overheads and 20% less energy consumption. EOLSR-RE is suitable choice in military applications, disaster recovery areas and remote areas such as forests where energy saving is important need.

8. FUTURE WORK The work can be extended to test EOLSR-RE and EOLSR-EC for higher packet rate and different network area by keeping other network parameters constant. Finally, the best scenario can be suggested where all network QoS parameters gives best results.

REFERENCES [1]

Imrich Chlamtac, Marco Conti, Jennifer J.-N. Liu, (2003) “Mobile ad hoc networking: imperatives and challenges”, Ad-hoc Networks, Elsevier, pp. 13-64.

[2]

Md. Anisur Rahman, Md. Shohidul Islam, Alex Talevski, (2009) “Performance Measurement of Various Routing Protocols in Ad-hoc Network”, Proceedings of the International MultiConference of Engineers and Computer Scientists, Hong Kong, Vol I.

[3]

C. Adjih, A. Laouiti, P. Minet, P. Muhlethaler, A. Qayyum, L. Viennot, (2010) “The Optimised Routing Protocol for Mobile Ad-hoc Networks: protocol specification”, INRIA-00471712, version 1 - 8.

[4]

Aman Shaikh, Mukul Goyal, Albert Greenberg, Raju Rajan, and K.K. Ramakrishnan, (2002)“An OSPF Topology Server:Design and Evaluation”, IEEE Journal on Selected Areas in communications, vol. 20, no. 4, pp.746-755.

[5]

Thomas Kunz, (2008) “Energy-Efficient Variations of OLSR”, IEEE Transactions, pp. 517-522.

[6]

I. Stojmenovic and X. Lin, (2001) “Power-aware localized routing in wireless networks”, IEEE Transactions on Parallel and Distributed Systems, Vol. 12(11), pp.1122-1133.

[7]

C.-K. Toh, (2001) “Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks”, IEEE communication magazine, pp. 138-147.

[8]

Saoucene Mahfoudh, Pascale Minet, (2008) “An energy efficient routing based on OLSR in wireless ad hoc and sensor networks” , 22nd International Conference on Advanced Information Networking and Applications Workshops, IEEE computer Society, pp. 1253-1259.

[9]

D.Kim, J.J.Garcia-Luna-Aceves, K.Obraczka, J.Cano and P.Manzoni, (2001) “Power-Aware Routing Based on The Energy Drain Rate for Mobile Ad-Hoc Networks”, Proceedings of the IEEE International Conference on Computer Communication and Networks.

[10] J.-H Chang and L. Tassiulas, (2000) “Energy Conserving Routing in Wireless Ad-hoc Networks”, in Proceedings of INFOCOM, Tel Aviv, Israel, pp. 22-31. [11] Md. Arafatur Rahman, Farhat Anwar, Jannatul Naeem, Md. Sharif Minhazul Abedin, (2010) “A Simulation Based Performance Comparison of Routing Protocol on Mobile Ad-hoc Network”, International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia.


319

[12] QualNet details :http://www.scalablenetworks.com. [13] David Oliver Jorg, (2003) “Performance Comparison Of MANET Routing Protocols In Different Network Sizes”, Computer Science Project, Institute of Computer Science and Applied Mathematics Computer Networks and Distributed Systems (RVS), University of Berne, Switzerland. [14] Humaira Nishat, Sake Pothalaiah, Dr. D.Srinivasa Rao, (2011) “Performance Evaluation of Routing Protocols in MANETS” International Journal of Wireless & Mobile Networks (IJWMN) Vol. 3, No. 2, pp. 67-75. [15] Alemneh Adane, (2010) “Active Communication Energy Efficient Routing Protocol Of Mobile Ad Hoc Network (MANETS)” A thesis submitted to the school of Graduate studies of Addis Ababa University in partial fulfillment of the requirements for the degree of Masters of Science in Electrical and Computer Engineering. [16] Wenjing Yang, Xinyu Yang, Guozheng Liu, and Chiyong Dong, (2011) “A Bandwidth Aware Multi-path Routing Protocol in Mobile Ad Hoc Networks”, Journal of Computational Information Systems, pp. 685-696. [17] Zhan Huawei, Zhou Yun, (2008) “Comparison and Analysis AODV and OLSR Routing Protocols in Ad Hoc Network”, IEEE Transactions, pp. 1-4. [18] Marco Fotino, Salvatore Marano (2008), “EE-OLSR:Energy Efficient OLSR Routing Protocol for Mobile Adhoc Networks”, IEEE transactions, pp.1-7.

Authors 1. Mayur Tokekar received the B.E. degree in 2008 from Dr.Babasaheb Ambedkar Mararhwada University. He is currently a M.Tech student at College of Engineering, Pune. He is pursuing his M.Tech in the field of Digital Systems. His areas of interests are wireless communication, embedded systems and image processing. 2. Radhika D. Joshi received the BE degree in 1993 from Pune University and ME Degree from Pune University in 2002. She is currently a PhD student at the University of Pune. She is pursuing research in the field of Wireless Mobile Ad hoc networks energy management issues. At present she is serving as Assistant Professor at Electronics and Telecommunication Engineering department of College of Engineering Pune, which is an autonomous institute of Government of Maharashtra. Her areas of interests are wireless communication, signal processing and electronic devices and circuits. She has received grants for two research proposals from two funding agencies recently. She has published several papers in journals and international conferences.